The Cloudcast

Massive Studios

The Cloudcast (@cloudcastpod) is the industry's #1 Cloud Computing podcast, and the place where Cloud meets AI.  Co-hosts Aaron Delp (@aarondelp) & Brian Gracely (@bgracely) speak with technology and business leaders that are shaping the future of business. Topics will include Cloud Computing | AI | AGI | ChatGPT | Open Source | AWS | Azure | GCP | Platform Engineering | DevOps | Big Data | ML | Security | Kubernetes | AppDev | SaaS | PaaS . 

  1. 2 HR AGO

    AI Agents for Unstructured Data

    Stephan Donze, Founder and CEO of AODocs, discusses the enterprise unstructured data crisis, where 80% of business data remains untapped due to legacy system limitations and the challenges of AI-powered document management at scale. We explore how AI agents can transform document workflows while maintaining trust and compliance, the architectural principles needed for cloud-native document management, and why traditional search fails in the age of generative AI. SHOW: 961 SHOW TRANSCRIPT: The Cloudcast #961 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET  NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST - "CLOUDCAST BASICS" SPONSORS: [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES: AODocs websiteTopic 1 - Welcome to the show, Stephan. Give everyone a quick introduction. Topic 2 - We hear all the time about unstructured data and the continual growth in the Enterprise. I’ve heard numbers of upwards of 80% of all corporate data is unstructured. I’ve worked at several companies and supported a significant number of customers over the years, and I can count on one hand how many say they have “control” of their data. How did this come to be, and is the problem as big as I think? Topic 3 - The second part of this, and this might be an even bigger problem, is how much of the data is used? Too many needles in the haystack, if you will. How does Agentic AI address this challenge, and where do traditional document management systems fail? Topic 4 - We’ve talked about data quality in the past on the show, and I’m wondering if this also becomes an issue. Let’s say you have a bunch of draft documents leading up to the final version. Is it possible that improper version control and/or we’re back to a data quality problem of finding the “final version” needle in the haystack? How does AI prevent this and also not hallucinate an answer that may not be true? Topic 5 - Some have called AI’s ability to absorb and report on data just fancy search. What are your thoughts on this? Where and how does traditional search differ from Agentic AI management? Topic 6 - I also see this as being so much more than indexing and reporting on documents. There is also the concept of automation and workflows that agentic AI can improve upon. What use cases are your customers implementing? Topic 6a - Where do you think the industry will go in the next 2-3 years? Topic 7 - If anyone is interested, what’s the best way to get started? FEEDBACK? Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

    26 min
  2. 17 SEPT

    The Return of Bare Metal?

    Todd Robinson, Founder and President of OpenMetal.io, discusses the resurgence of bare metal infrastructure driven by AI workloads, digital sovereignty requirements, and companies reassessing public cloud economics. The conversation explores how organizations are finding cost and control advantages in bare metal solutions, particularly for long-running applications. It examines OpenMetal's open-source approach using technologies like Ceph and OpenStack to deliver flexible infrastructure alternatives. SHOW: 959 SHOW TRANSCRIPT: The Cloudcast #959 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET  CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"  SPONSORS: [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search “Interconnected by Equinix”.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcastSHOW NOTES: OpenMetal websiteTopic 1 - Welcome to the show. Tell us about your background, and you developed a passion around bare metal and cloud services? Topic 2 - Between AI (GPU rental), digital sovereignty initiatives, and even virtualization alternatives, it feels like bare metal is having a resurgence. Give some a sense of what the demands for bare metal solutions look like today? Topic 3 - As companies understand the economics of having used public cloud services, are there certain use-cases that become immediately obvious where more private, hosted, bare metal services just make more sense?  Topic 4 - OpenMetal is based on open source technologies like Ceph and OpenStack. How important to customers about the technologies under their applications, or do the economics and control aspects play a bigger role in their decisions?  Topic 5 - I’m often asked if there is a model about when it makes more sense to use on-demand service vs. more fixed services. Is there a rule of thumb (e.g. longevity of an application, amount of change, etc.) that you’ve found drives the most success at picking the right environment for applications? Topic 6 - OpenMetal could be described as a public or private cloud service. Do you find that there is still the stigma over “private cloud” that we saw when the hyperscalers were initially growing so quickly? Topic 7 - What are the best ways to engage with or begin using bare metal services?  FEEDBACK? Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

    29 min
  3. 10 SEPT

    Kubernetes-native Continuous Testing

    Ole Lensmar (@olensmar, Founder/CTO at @TestKube_io) discusses how Kubernetes-native testing platforms are designed to address limitations in traditional CI/CD testing workflows. The conversation covers how TestKube differs from existing testing environments, expands test coverage opportunities for development and QA teams, and provides best practices for testing in Kubernetes environments. SHOW: 957 SHOW TRANSCRIPT: The Cloudcast #957 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET  CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw NEW TO CLOUD? CHECK OUT OUR OTHER PODCAST: "CLOUDCAST BASICS"  SPONSORS: [Interconnected] Interconnected is a new series from Equinix diving into the infrastructure that keeps our digital world running. With expert guests and real-world insights, we explore the systems driving AI, automation, quantum, and more. Just search Interconnected by Equinix.[TestKube] TestKube is Kubernetes-native testing platform, orchestrating all your test tools, environments, and pipelines into scalable workflows empowering Continuous Testing. Check it out at TestKube.io/cloudcast[DoIT] Visit doit.com (that’s d-o-i-t.com) to unlock intent-aware FinOps at scale with DoiT Cloud Intelligence.SHOW NOTES: TestKube - A Kubernetes-native platform that powers Continuous Testing for today’s AI-accelerated developmentTestKube (open source)Why did we start TestKube (Ole Lensmar) Topic 1 - Welcome to the show. Tell us about your background and what led you to start TestKube. Topic 2 - Let’s talk about the origins of TestKube. What were some areas where you saw people having frustrations or limitations that were holding back their ability to do proper testing to get things into production? Topic 3 - Let’s talk about the basics of TestKube. Can you talk about how it’s different from existing testing environments, or how people use CI/CD today Topic 4 - Does TestKube expand what a typical Dev-team, or QA-team would test, or does it create new opportunities for test coverage that were very difficult before?  Topic 5 - What are some of the results or feedback you’ve heard from people using TestKube? Topic 6 - What are some best practices you’re seeing as people begin to evolve how they test for their Kubernetes environments? Topic 7 - What’s the best way for people to get started with TestKube FEEDBACK? Email: show at the cloudcast dot netBluesky: @cloudcastpod.bsky.socialTwitter/X: @cloudcastpodInstagram: @cloudcastpodTikTok: @cloudcastpod

    32 min
  4. 1 SEPT

    Every Week Feels like an AI Gartner Hype Cycle

    From extreme ups to startling downs, every week can feel like the peak of expectations and the trough of disillusionment for AI.   SHOW: 954 SHOW TRANSCRIPT: The Cloudcast #954 Transcript SHOW VIDEO: https://youtube.com/@TheCloudcastNET  CLOUD NEWS OF THE WEEK: http://bit.ly/cloudcast-cnotw CHECK OUT OUR NEW PODCAST: "CLOUDCAST BASICS" SHOW SPONSORS: [DoIT] Visit doit.com (that’s d-o-i-t.com) to unlock intent-aware FinOps at scale with DoiT Cloud Intelligence.[VASION] Vasion Print eliminates the need for print servers by enabling secure, cloud-based printing from any device, anywhere. Get a custom demo to see the difference for yourself.SHOW NOTES: THE UPS AND DOWNS OF AI - THE CONSTANT HYPE CYCLE Healthy Competition [YES] Consumer and Enterprise Markets [YES] Market leader(s) [YES, sort of] Well-Defined, profitable business model [NO] Open, lower-cost alternative emerged [YES/NO] Usage patterns emerging [YES/NO] [ups] Constant high-profile VC, Sovereign wealth, hyperscaler funding of AI startups[ups] Constant high-profile CAPEX spending by hyperscalers, model builders, data center builders[ups] Rapidly growing user-bases[ups] Growing revenues at some companies (NVIDIA, OpenAI, Google, Microsoft, Anthropic)[downs] Growing losses at high-profile companies  [???] Frequent, high-profile movement by key people at high-profile companies (engineers, leadership)[downs] Frequent, partial acquires of founders and key engineers, but not entire companies[downs] Secondary market scales of startup shares, bypassing traditional secondary and public markets[downs] No “NetFlix of AI” company[downs] No “AI Agent” success stories[???] Consumer “winner-take-all” mindset from AI companies[downs] Enterprise companies struggling to create ROI+ projects (in early days)[???] Enterprise “bundles” raising prices (CoPilot, Gemini, etc.)[downs] Unclear if new frontier models are getting better than previous versions (e.g. GPT-5)[???] Are inference prices coming down? [ups] Consumers have many excellent AI choicesIt’s unclear if AI companies have created any moats yet; it’s unclear if LLMs can be differentiatedChatbots, developer-assistants and document management are use-cases. What else?Are agents ready to be mainstream yet? Pick-axe providers are making the money right now (NVIDIA, Broadcom, etc.), but is there moat entirely on super-premium HW?User-experiences are still being understoodWill AI + Ads (business model) be a big bang event, or happen gradually? FEEDBACK? Email: show at the cloudcast dot netTwitter/X: @cloudcastpodBlueSky: @cloudcastpod.bsky.socialInstagram: @cloudcastpodTikTok: @cloudcastpod

    32 min

About

The Cloudcast (@cloudcastpod) is the industry's #1 Cloud Computing podcast, and the place where Cloud meets AI.  Co-hosts Aaron Delp (@aarondelp) & Brian Gracely (@bgracely) speak with technology and business leaders that are shaping the future of business. Topics will include Cloud Computing | AI | AGI | ChatGPT | Open Source | AWS | Azure | GCP | Platform Engineering | DevOps | Big Data | ML | Security | Kubernetes | AppDev | SaaS | PaaS . 

You Might Also Like